Enhancing job application writing: A comparative case study of AI and human feedback on grammar and mechanics - Noerjaman, Lutfi Arief; Dallyono, Ruswan; Hidayati, Farida (Journal of English Language Teaching Innovations and Materials (Jeltim), 2025)
Submission of well-structured job application letters is an essential aspect of business and government recruitment processes. However, due to difficulties with grammar and mechanics, many students, fresh graduates included, fail to produce high-quality job applications. While human reviewers typically give feedback to enhance these skills, Artificial Intelligence (AI) has brought about automated feedback systems. The research compared the performance of two artificial intelligence models, Gemini and ChatGPT, and human experts in assessing job application letters. The study compared feedback in six writing features"”subject-verb agreement, parallelism, spelling, capitalization, punctuation, and sentence variety"”of 10 job application letters composed by final-year high school students. Results indicated that ChatGPT and Gemini performed better than human experts in most metrics. These findings add to the discussion of using AI to improve application letter quality and offer implications regarding the potential of AI-assisted writing feedback. Integrating such tools into writing instruction can offer consistent, real-time feedback, thereby supporting skill development and improving students' employability prospects. The study contributes to the growing field of AI in education by highlighting the practical benefits and potential limitations of AI-generated feedback in high-stakes writing tasks such as job applicationsHow to cite this paper: Noerjaman, L. A., Dallyono, R., Hidayati, F. (2025). Enhancing job application writing: A comparative case study of AI and human feedback on grammar and mechanics. Journal of English Language Teaching Innovations and Materials (Jeltim), 7(1), 54-72. http://dx.doi.org/10.26418/jeltim.v7i1.89240